PD-1 immune checkpoint blockade induces a high rate of anti-melanoma response and provides clinical benefits unprecedented with immunotherapy (Hamid et al., 2013; Topalian et al., 2012). This therapeutic approach has also been shown to be active against a growing list of human malignancies, and clinical testing of combinations of PD-1 with other treatment targets has already begun (Sharma and Allison, 2015). However, effective use of anti-PD-1 clinical agents is encumbered mostly by innate resistance, the mechanistic basis of which remains poorly characterized.
In melanoma, the extent of pretreatment and especially treatment-induced T cell infiltration correlates with clinical responses (Tumeh et al., 2014), supporting unleashing of tumor-specific T cells as a mechanistic basis of anti-PD-1 therapy. Preliminary retrospective analyses of clinical data hinted at prior failure of MAPK-targeted therapy being a negative factor for subsequent response to immune checkpoint blockade in melanoma (Puzanov et al., 2015; Ramanujam et al., 2015; Simeone et al., 2015). At the genomic level, the overall mutation load, which may reflect or lead to higher neoepitope load, a smoking signature, and impairment of DNA repair, have been correlated with anti-PD-1 response in non-small cell lung cancers (Rizvi et al., 2015). However, the lack of these response-related features do not robustly preclude response. Thus, there remains a need for an objective assessment of omic-scale features related to both response and resistance as an important step toward patient stratification and identification of combinatorial targets.
There remains a need for improved tools to permit the detection, identification and prognosis of drug resistant cancers, particularly anti-PD-1-resistant melanomas. There also remains a need for targets useful in the detection and treatment of cancer.